Tables and charts are both tools that can be generated on a computer, via software programs, and used by a computer user to convey information. While both tables and charts are popular tools for storing, conveying and analyzing data, they have some generalized differences. Charts are commonly more graphic in nature, presenting data, for example, as points on a line on an x-y axis, or various bars in a bar graph. Tables, in contrast, are typically more tabular, presenting data, for example, as numbers in various rows and columns. Also, charts generally focus on data summaries and/or totals, while tables generally present more data details. Charts can graphically represent a series of data stored in a table.
Some computer-generated tables, e.g., PivotTables, are interactive data analysis tools that allow users to consolidate and analyze data from a variety of sources, including, but not limited to, Excel worksheets, relational databases, text files and OLAP cubes. Likewise, some computer-generated charts, e.g., PivotCharts, have the capability to be interactive visual data analysis tools.
Interactive charts provide a user the capability to perform a variety of interactive alterations and navigations on the presented data, which renders interactive charts analysis tools in their own right. For example, a user can filter data elements, such as datapoints, displayed in an interactive chart to a subset of the data group, or to one or more specific fields of a data set. A user can also add or remove fields of data elements from the interactive chart. Additionally, a user can navigate an interactive chart to analyze particular data fields and/or datapoints. Examples of user navigations on an interactive chart include, but are not limited to, drilling, expanding and collapsing.
An example of drilling is where a datapoint, or element, of a more general, parent, data field, e.g., food profits, is initially displayed in an interactive chart. A user can drill on this general, food profit, data field to exhibit more specific, child, datapoints, e.g., a dairy profit datapoint, a vegetable profit datapoint, and a snack item profit datapoint. In contrast, a user can collapse an interactive chart for a more generalized view of a data set. In the previous example, if datapoints for dairy profits, vegetable profits and snack item profits are currently displayed in an interactive chart, the user can collapse the chart so that all these three child datapoints are combined into, and replaced by, one more general, parent, food profit datapoint.
An interactive chart can also be expanded to display additional data fields. In the previous example, if a datapoint, or element, for a parent, food profit, data field is currently displayed in an interactive chart, the chart can be expand to also exhibit a datapoint for a second parent, food cost, data field. As another example of an expansion navigation, if datapoints for dairy profits, vegetable profits and snack item profits are currently displayed in an interactive chart, the chart can be expanded to exhibit another child, fruit profits, datapoint.
Users can also refresh the data from the underlying data source used to generate an interactive chart, whether it be a local or external data source, in order to ensure that the chart graphically depicts the most current information.
Additionally, users can alter the appearance of an interactive chart, for, e.g., aesthetic reasons. For example, an interactive chart user may want to move a chart element, such as the chart legend, from the left bottom corner to the right bottom corner of the chart, or may want to change the font or color of the legend.
All of these alterations and navigations allow for a highly flexible, interactive chart analysis tool. Various interactive chart alterations, however, can take time to accomplish, especially if the user is making many changes. If a user's formatting changes cannot be maintained upon various alterations and navigations of the interactive chart, or data refreshing, the user's efficiency is compromised. Additionally, the interactive chart is generally less effective, and it may even be abandoned, with users losing access to a flexible, interactive data analysis tool due to formatting frustrations.